.. note:: :class: sphx-glr-download-link-note Click :ref:`here ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_auto_examples_plot_plot_human_activity.py: Human Activity Recognition Visualization ========================================== .. rst-class:: sphx-glr-horizontal * .. image:: /auto_examples/plot/images/sphx_glr_plot_human_activity_001.png :class: sphx-glr-multi-img * .. image:: /auto_examples/plot/images/sphx_glr_plot_human_activity_002.png :class: sphx-glr-multi-img * .. image:: /auto_examples/plot/images/sphx_glr_plot_human_activity_003.png :class: sphx-glr-multi-img * .. image:: /auto_examples/plot/images/sphx_glr_plot_human_activity_004.png :class: sphx-glr-multi-img * .. image:: /auto_examples/plot/images/sphx_glr_plot_human_activity_005.png :class: sphx-glr-multi-img .. rst-class:: sphx-glr-script-out Out: .. code-block:: none Target looks like classification Showing only top 10 of 561 continuous features Linear Discriminant Analysis training set score: 0.984 | .. code-block:: default # sphinx_gallery_thumbnail_number = 3 import matplotlib.pyplot as plt from sklearn.datasets import fetch_openml from dabl import plot X, y = fetch_openml('har', as_frame=True, return_X_y=True) plot(X, y) plt.show() .. rst-class:: sphx-glr-timing **Total running time of the script:** ( 0 minutes 23.115 seconds) .. _sphx_glr_download_auto_examples_plot_plot_human_activity.py: .. only :: html .. container:: sphx-glr-footer :class: sphx-glr-footer-example .. container:: sphx-glr-download :download:`Download Python source code: plot_human_activity.py ` .. container:: sphx-glr-download :download:`Download Jupyter notebook: plot_human_activity.ipynb ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_